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Crop thinning subsequent to fruit set can help regulate yield and improve fruit composition at harvest. Accordingly, an experiment was established in two vineyards (Site 1 Riverland District of South Australia; Site 2 Sunraysia District of Victoria) to investigate effects of crop removal after fruit set (when berries were pea size) using a machine harvester. Specific zones of the canopy were targeted for thinning to remove a predetermined percentage of the fruit and avoid over‐thinning. Cropping responses to mechanical thinning were compared with control (un‐thinned) vines, and with hand thinned vines (where fruit was removed from a similar portion of the canopy as for mechanical thinning). In a fourth treatment, bunches damaged by mechanical thinning were removed by hand. Inclusion of hand thinning treatments enabled us to distinguish between the potential benefits of reduced yield and the potential damage caused by the mechanical harvester to foliage and/or remaining fruit. Both the mechanical and the hand thinning treatments reduced bunch number as well as yield by a similar amount (approximately 24% on Site 1 and approximately 45% on Site 2) and advanced fruit maturity (soluble solids accumulation at harvest), relative to un‐thinned controls, by approximately 1.6 % and 1.7% respectively. Soluble solids accumulated at a similar rate for all treatments at sites, despite differences in yield, implying that the impact of thinning treatments originated prior to veraison. Berry weight was increased by hand thinning at Site1, and by all thinning treatments at Site 2. Anthocyanin concentration (berry fresh weight basis) was higher in fruit from the mechanically thinned vines compared to controls (un‐thinned). Mechanical thinning successfully reduced crop level to the target yield, and improved fruit quality. Mechanical thinning, via modified use of a machine harvester, thus offers some potential to regulate yield over large and minimally pruned vineyards, in a timely and cost‐effective fashion.

Background and Aims Interactions are the main causes of complexity in field experiments; however, no studies have combined water and temperature regimes in field‐growing vines. Here we assessed grape and wine attributes from a field trial where these factors were directly manipulated. Methods and Results The experiment consisted of Shiraz vines grown in a 22 factorial experiment with two temperature (control and heated) and two water regimes (deficit and irrigated) during two seasons (2010/11 and 2011/12). The sensory and compositional characteristics of grapes and wines were assessed in both seasons, whereas a detailed profile of the phenolic substances was determined by spectrophotometry in 2011/12. We found additive effects (i.e. lack of interaction) between temperature and water for berry mass and components, fruit composition (titratable acidity and pH), grape phenolic substances (12.5% ethanol‐extracted and most of the 70% acetone‐extracted), wine phenolic substances (chemical age 2), and wine sensory traits (floral aromas and berry flavours). Significantly, previously unrecorded interactions between temperature and water were found for grape phenolic substances (70% acetone‐extracted skin and seed tannins and total phenolic substances per berry), wine phenolic substances (colour density, tannins and phenolic substances) and wine sensory traits (floral aromas, cooked fruit flavours and tannin structure). Conclusion The effect of water deficit leading to colourful and flavoursome wines rich in phenolic substances may not be held under high temperature. Significance of the Study Our study anticipates the drier and hotter climate of the Barossa Valley, and provides industry with indications of a shift in wine profiles that would require technological innovation to maintain the identity of Barossa Shiraz.

BackgroundStomatal behavior in grapevines has been identified as a good indicator of the water stress level and overall health of the plant. Microscope images are often used to analyze stomatal behavior in plants. However, most of the current approaches involve manual measurement of stomatal features. The main aim of this research is to develop a fully automated stomata detection and pore measurement method for grapevines, taking microscope images as the input. The proposed approach, which employs machine learning and image processing techniques, can outperform available manual and semi-automatic methods used to identify and estimate stomatal morphological features.ResultsFirst, a cascade object detection learning algorithm is developed to correctly identify multiple stomata in a large microscopic image. Once the regions of interest which contain stomata are identified and extracted, a combination of image processing techniques are applied to estimate the pore dimensions of the stomata. The stomata detection approach was compared with an existing fully automated template matching technique and a semi-automatic maximum stable extremal regions approach, with the proposed method clearly surpassing the performance of the existing techniques with a precision of 91.68% and an F1-score of 0.85. Next, the morphological features of the detected stomata were measured. Contrary to existing approaches, the proposed image segmentation and skeletonization method allows us to estimate the pore dimensions even in cases where the stomatal pore boundary is only partially visible in the microscope image. A test conducted using 1267 images of stomata showed that the segmentation and skeletonization approach was able to correctly identify the stoma opening 86.27% of the time. Further comparisons made with manually traced stoma openings indicated that the proposed method is able to estimate stomata morphological features with accuracies of 89.03% for area, 94.06% for major axis length, 93.31% for minor axis length and 99.43% for eccentricity.ConclusionsThe proposed fully automated solution for stomata detection and measurement is able to produce results far superior to existing automatic and semi-automatic methods. This method not only produces a low number of false positives in the stomata detection stage, it can also accurately estimate the pore dimensions of partially incomplete stomata images. In addition, it can process thousands of stomata in minutes, eliminating the need for researchers to manually measure stomata, thereby accelerating the process of analysing plant health.

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Canopy topping and leaf removal are management practices commonly used in New Zealand vineyards to increase light and pesticide penetration to the fruit zone, thus, reducing disease incidence. Previous research has suggested that an increase in photosynthesis occurs when leaves are removed, and this may compensate for the reduced leaf area. However, it is difficult to extrapolate single-leaf photosynthesis measurements to a whole-plant scale. Therefore the extent of the compensation is unknown. To evaluate the impact of leaf removal and canopy height on whole-vine photosynthesis, treatments were imposed during the lag phase of berry growth. Leaves were removed from the lower quarter of the canopy, or vines were topped to three quarters of the height of control plants, in a two-by-two-factorial design. Both topping and leaf removal caused a decrease in whole-vine photosynthesis immediately after the treatments were imposed. Leaf removal, but not topping height, reduced photosynthesis on a per unit leaf area basis. This suggests that the lower portion of the canopy contributes more than the upper portion of the canopy to whole-vine photosynthesis. When measurements were made again approximately two months later, tall vines without leaf removal had a higher photosynthesis rate than the other treatments. Fruit yield, sugar content, vine carbohydrate reserves and pruning weights followed trends similar to those observed for photosynthesis, suggesting that although some photosynthetic compensation occurred, the defoliation treatments had a negative effect on vine growth.

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